We use graphical models and structure learning to explore how people learn policies in sequential decision making tasks. Studies of sequential decision-making in humans frequently...
Can we trust without any reliable truth information? Most trust architectures work in a similar way: a trustor makes some observations, rates the trustee, and makes recommendations...
We present an algorithm called Optimistic Linear Programming (OLP) for learning to optimize average reward in an irreducible but otherwise unknown Markov decision process (MDP). O...
We embark on an initial study of a new class of strategic (normal-form) games, so-called ranking games, in which the payoff to each agent solely depends on his position in a ranki...
Even under polynomial restrictions on plan length, conformant planning remains a very hard computational problem as plan verification itself can take exponential time. This heavy ...